Conventionally, in implementing promotional platforms to display relevant products, users first perform bid processing on search terms in bid management server systems. When a search term is entered at a front-end search page of a website, product data information relating to the search term is displayed. Fixed threshold values are separately set up for the search term and for pieces of the product data information corresponding to the search term. The displayed results are static.
In a specific implementation process, a seller-user first selects keywords and promoted products corresponding to the keywords on a bid management server system. Subsequently, an algorithm module calculates correlations and obtains a correlation threshold score between a keyword and product data information. This calculated correlation threshold score is saved into a database. An engine server downloads the correlation threshold scores from the database and establishes an index database. After a user at a front-end client engages in a search using search terms, the threshold scores for product data information corresponding to the search terms are acquired from the index database, and the various threshold scores are compared with a preset static threshold value. Product data information having a threshold score greater than the static threshold score is selected for display. This filtering method is often overly simple and static because the filtering method treats all query words according to a uniform standard. As correlation threshold scores between keywords and product data information undergo dynamic changes, the filtering method often fails to produce more responsive and accurate search results.
In the above product data information method, the product data information that is displayed using the search term is often of poor quality and typically has a poor correlation with the search terms. In addition, the correlation of displayed promoted products with the search term may be worse than the result of a natural search. A search for a product on a website involves requests to two search engines (a product search engine and an ad search engine). The natural search refers to results from the product search engine, but the results of the ad search engine are displayed before the products that are found from the natural search, thus impacting user experience and click through rates.